Create app.py

app.py

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+import requests
+from bs4 import BeautifulSoup
+
+url = "https://aspireec.com/"
+response = requests.get(url)
+soup = BeautifulSoup(response.text, 'html.parser')
+# Extract data (e.g., headlines, paragraphs, etc.)
+content = soup.find_all('p')  # Example: extracting paragraphs
+website_data = [p.text for p in content]
+import json
+
+with open('website_data.json', 'w') as file:
+    json.dump(website_data, file)
+from sentence_transformers import SentenceTransformer
+
+model = SentenceTransformer('all-MiniLM-L6-v2')
+embeddings = model.encode(website_data)
+import faiss
+import numpy as np
+
+# Create FAISS index
+dimension = embeddings.shape[1]
+index = faiss.IndexFlatL2(dimension)
+index.add(np.array(embeddings))
+query = "What is the website about?"
+query_embedding = model.encode([query])
+distances, indices = index.search(np.array(query_embedding), k=1)
+best_match = website_data[indices[0][0]]
+from transformers import pipeline
+
+summarizer = pipeline("summarization", model="google/flan-t5-base")
+answer = summarizer(best_match)
+print(answer)
+import streamlit as st
+
+st.title("Website Chatbot")
+
+user_input = st.text_input("Ask me anything about the website:")
+if user_input:
+    response = get_answer(user_input)  # Function to query data
+    st.write(response)